Purpose The aim of this study was to assess the prevalence of high cardiovascular risk and the trend of cardiovascular risk factors in a large sample of Belgian workers. Methods A cross-sectional study was performed on the data of workers under medical surveillance by the non-profit occupational health service IDEWE in 2018. The prevalence of poor health for smoking, physical activity, body mass index (BMI), and blood pressure according to the American Heart Association (AHA) definition was investigated. The presence of three or more poor cardiovascular health metrics was considered high cardiovascular risk. A log-binomial regression model was used to compare the prevalence of high cardiovascular risk between economic sectors taking into account age and gender and to calculate predicted probabilities of high cardiovascular risk. Results Data about 212,792 workers were available. In 2018, overall, 7% of workers had high cardiovascular risk. Transport and construction had the highest prevalence of high cardiovascular risk, 14% and 12%, respectively. The lowest prevalence, 3%, was observed in education. Differences between sectors remained statistically significant after adjustment for age and gender. In men, workers in transport and storage and in construction had the highest predicted probability of high cardiovascular risk that increased with age. In women, highest predicted probability was observed in transport and storage. Conclusions When implementing health promotion initiatives, priority should be given to sectors and professions where risk factors are most prevalent or are increasing rapidly. Measures should be tailored to the special needs of the occupational groups at high risk.

Significant differences in indices of workers' health were observed between sectors. This information is now being used in the implementation of a sector-oriented health surveillance programme.

Background Healthcare workers (HCWs) can be a source of SARS-CoV-2 within long-term care facilities (LTCFs); therefore, we analysed the data from a testing programme among LTCF employees. Aims The aim of this study was to investigate the prevalence of SARS-CoV-2 and its determinants among employees of LTCFs and the risk for fellow workers and residents. Methods Testing started at week 15, the first wave’s peak, using nasopharyngeal swabs for PCR up to week 23. At the start of the second wave (week 32), testing resumed. Results A total of 32 457 test results were available from 446 LTCFs: 2% were positive: 1% in men, 2% in women, 2% in HCWs (=having patient contact), 1% in non-HCWs, higher in younger age groups. In total, 30 729 employees were tested once, 823 twice, 66 thrice and 4 four times. Prevalence was 13% during the first week of testing (week 15) and declined to 7% (week 16) to stay at around 1% (from week 17 until week 23). At the start of the second wave (week 31–33), the prevalence was around 3%. In 70% of positive tests, the employee was asymptomatic. Conclusions Our study confirms the presence of HCWs with SARS-CoV-2 as a possible source of infection in LTCFs even when the incidence in the general population was low; 70% were asymptomatic. To control the spread of SARS-CoV-2 in LTCFs vaccination, infection prevention and control measures are necessary as well as testing of all LTCF HCWs during possible outbreaks, even if asymptomatic.

The design and implementation of applications for behavior change should be preceded by careful analysis of the behavior change process and the target population. We, therefore, present on the basis of a blended research approach a rationale, opportunities and basic requirements for an application that offers a program for reducing intake of sugar sweetened beverages (SSB) by adolescents. This paper discusses the role of e-coaching and gamification as two high-touch design patterns in the behavior change process. Both design patterns aim at supporting the individual in a transformational journey from a current state toward a desired state where the detrimental behavior should be replaced by healthy alternative behavior. First, an elementary behavior scheme is introduced that frames three empirical studies. In the first study (plenary focus groups; n = 13), participants advised to include system recommendations for alternative healthy behavior, stressed the need for personalization of the e-coach and showed strong appreciation for the inclusion of gamification elements. The second study (online survey; n = 249) showed that SSB-intake is highly contextual and that reasons for (limiting) consumption SSB varies greatly between individuals, which the e-coach application should take into account. In a final small-scale pilot study (n = 27), we observed the potential of the inclusion of gamification elements, such as challenges and rewards, to increase compliance to the self-monitoring process of SSB consumption. Building upon these insights and prior studies, we argue that an e-coach mimics the collaborative practice of the program; its main task is to enrich the interaction with cooperative conversational experiences, in particular with respect to the alignment between user and system, motivational encouragement, personalized advice, and feedback about the activities. In addition, we outline that gamification not only has the potential to increase self-monitoring of the target behavior, user engagement, and commitment with the intervention program, but also enables a designer to shift long-term negative outcome of excessive intake in real life to short-term consequences in a virtual environment. In future larger follow-up studies, we advise to integrate the two design patterns within a social network of virtual and human agents that play a variety of competitive, normative and supportive roles.

score (with all exertions explicitly represented). This presentation describes the RSI and COSI algorithm. A brief complex task example compares the RSI to the 1995 SI and showcases the RSI's much improved utility as a tool for the design and evaluation of complex tasks.